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Medicaid managed care: how to target efforts to reduce costs.

Charlson ME, Wells MT, Kanna B, Dunn V, Michelen W - BMC Health Serv Res (2014)

Bottom Line: To be successful, cost control efforts must target Medicaid Managed Care (MMC) beneficiaries likely to incur high costs.Yearly costs were more related to the total burden of comorbidity than any specific comorbid disease.Comorbidity can be used to identify MMC beneficiaries most likely to have high costs.

View Article: PubMed Central - PubMed

Affiliation: Division of Clinical Epidemiology and Evaluative Sciences Research and Center for Integrative Medicine at Weill Cornell Medical College, New York, USA. mecharl@med.cornell.edu.

ABSTRACT

Background: To be successful, cost control efforts must target Medicaid Managed Care (MMC) beneficiaries likely to incur high costs. The critical question is how to identify potential high cost beneficiaries with simple, reproducible, transparent, auditable criteria. Our objective in this analysis was to evaluate whether the total burden of comorbidity, assessed by the Charlson comorbidity index, could identify MMC beneficiaries who incurred high health care costs.

Methods: The MetroPlus MMC claims database was use to analyze six months of claims data from 07/07-12/07; the analysis focused on the total amount paid. Age, gender, Charlson comorbidity score, serious mental illness and pregnancy were analyzed as predictors of total costs.

Results: We evaluated the cost profile of 4,614 beneficiaries enrolled at MetroPlus, an MMC plan. As hypothesized, the comorbidity index was a key correlate of total costs (p < .01). Yearly costs were more related to the total burden of comorbidity than any specific comorbid disease. For adults, in addition to comorbidity (p < .01) both serious mental illness (p < .01) and pregnancy (p < .01) were also related to total costs, while age, drug addiction and gender were not. The model with age, gender, comorbidity, serious mental illness, pregnancy and addiction explained 20% of the variance in total costs. In children, comorbidity (p < .01), serious mental illness (p < .01), addiction (p < .03) and pregnancy (p < .01) were associated with log cost; the model with those variables explained 6% of the variance in costs.

Conclusions: Comorbidity can be used to identify MMC beneficiaries most likely to have high costs.

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Related in: MedlinePlus

The distribution of patients with specific chronic diseases according to their adjusted comorbidity score.
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Fig2: The distribution of patients with specific chronic diseases according to their adjusted comorbidity score.

Mentions: Overall, as comorbidity increased, total costs increased (p < .01). Costs for each chronic condition did not differ at lower levels of comorbidity. Costs according to specific chronic illnesses were also evaluated. Figure 1 shows the costs for chronic diseases impacting at least 100 beneficiaries according to the adjusted level of comorbidity. It demonstrates that costs are more a function of the total burden of comorbidity than of any specific comorbid disease. Figure 2 shows the distribution of patients according to the adjusted comorbidity index; the vast majority of beneficiaries, regardless of specific chronic illness, had a comorbidity index of zero or one.Table 2


Medicaid managed care: how to target efforts to reduce costs.

Charlson ME, Wells MT, Kanna B, Dunn V, Michelen W - BMC Health Serv Res (2014)

The distribution of patients with specific chronic diseases according to their adjusted comorbidity score.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4289361&req=5

Fig2: The distribution of patients with specific chronic diseases according to their adjusted comorbidity score.
Mentions: Overall, as comorbidity increased, total costs increased (p < .01). Costs for each chronic condition did not differ at lower levels of comorbidity. Costs according to specific chronic illnesses were also evaluated. Figure 1 shows the costs for chronic diseases impacting at least 100 beneficiaries according to the adjusted level of comorbidity. It demonstrates that costs are more a function of the total burden of comorbidity than of any specific comorbid disease. Figure 2 shows the distribution of patients according to the adjusted comorbidity index; the vast majority of beneficiaries, regardless of specific chronic illness, had a comorbidity index of zero or one.Table 2

Bottom Line: To be successful, cost control efforts must target Medicaid Managed Care (MMC) beneficiaries likely to incur high costs.Yearly costs were more related to the total burden of comorbidity than any specific comorbid disease.Comorbidity can be used to identify MMC beneficiaries most likely to have high costs.

View Article: PubMed Central - PubMed

Affiliation: Division of Clinical Epidemiology and Evaluative Sciences Research and Center for Integrative Medicine at Weill Cornell Medical College, New York, USA. mecharl@med.cornell.edu.

ABSTRACT

Background: To be successful, cost control efforts must target Medicaid Managed Care (MMC) beneficiaries likely to incur high costs. The critical question is how to identify potential high cost beneficiaries with simple, reproducible, transparent, auditable criteria. Our objective in this analysis was to evaluate whether the total burden of comorbidity, assessed by the Charlson comorbidity index, could identify MMC beneficiaries who incurred high health care costs.

Methods: The MetroPlus MMC claims database was use to analyze six months of claims data from 07/07-12/07; the analysis focused on the total amount paid. Age, gender, Charlson comorbidity score, serious mental illness and pregnancy were analyzed as predictors of total costs.

Results: We evaluated the cost profile of 4,614 beneficiaries enrolled at MetroPlus, an MMC plan. As hypothesized, the comorbidity index was a key correlate of total costs (p < .01). Yearly costs were more related to the total burden of comorbidity than any specific comorbid disease. For adults, in addition to comorbidity (p < .01) both serious mental illness (p < .01) and pregnancy (p < .01) were also related to total costs, while age, drug addiction and gender were not. The model with age, gender, comorbidity, serious mental illness, pregnancy and addiction explained 20% of the variance in total costs. In children, comorbidity (p < .01), serious mental illness (p < .01), addiction (p < .03) and pregnancy (p < .01) were associated with log cost; the model with those variables explained 6% of the variance in costs.

Conclusions: Comorbidity can be used to identify MMC beneficiaries most likely to have high costs.

Show MeSH
Related in: MedlinePlus